Agent device, agent system, and recording medium

ABSTRACT

An agent device that receives, from an onboard device installed in a vehicle, vehicle information relating to the vehicle and question information corresponding to a question from a user, based on the vehicle information, confirms a scope of questions for which generation of a response is not possible, and instructs the onboard device to block receipt of questions falling within the scope of questions for which it has been confirmed that response generation is not possible.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based on and claims priority under 35 USC 119 fromJapanese Patent Application No. 2020-013028 filed on Jan. 29, 2020, thedisclosure of which is incorporated by reference herein.

BACKGROUND Technical Field

The present disclosure relates to an agent device, an agent system, anda recording medium recording a program therein used to provide aresponse to a question asked by a user.

Related Art

Japanese Patent Application Laid-Open (JP-A) No. 2001-141500 discloses avehicle agent processing device that provides information relevant tothe operation of various onboard units.

Suppose that the agent processing device of JP-A No. 2001-141500 were tobe applied to an agent used to search an owner's manual. In such cases,were a question from a user to be received when the agent is unable toprovide support for some or all functionality of a vehicle, for examplein cases in which an owner's manual stored with responses to questionshas not been compiled, or cases in which an owner's manual istemporarily unavailable due to an ongoing update, a response such as“unknown” or “not found” may be given to the question, causingfrustration for the user.

SUMMARY

An aspect of the disclosure is an agent device that includes: a memory;and a processor coupled to the memory. The processor is configured to:receive, from an onboard device installed in a vehicle, vehicleinformation relating to the vehicle and question informationcorresponding to a question from a user, based on the vehicleinformation, confirm a scope of questions for which generation of aresponse is not possible, and instruct the onboard device to blockreceipt of questions falling within the scope of questions for which ithas been confirmed that response generation is not possible.

BRIEF DESCRIPTION I/F THE DRAWINGS

Exemplary embodiments of the present disclosure will be described indetail based on the following figures, wherein:

FIG. 1 is a diagram illustrating an example of schematic configurationof a manual provision system according to a first exemplary embodiment;

FIG. 2 is a block diagram illustrating an example of hardwareconfiguration of a vehicle of the first exemplary embodiment;

FIG. 3 is a block diagram illustrating an example of hardwareconfiguration of a server of the first exemplary embodiment;

FIG. 4 is a block diagram illustrating an example of functionalconfiguration of an agent server of the first exemplary embodiment;

FIG. 5 is a block diagram to explain functionality of a manual provisionsystem of the first exemplary embodiment;

FIG. 6 is a diagram illustrating an example of a training datageneration method;

FIG. 7 is a sequence chart illustrating an example of a flow ofprocessing relating to confirmation of an agent association status andprocessing to reflect the association status on a monitor in a manualprovision system of the first exemplary embodiment;

FIG. 8 illustrates an example of display on a monitor in a case in whichagent association exists;

FIG. 9 is illustrates an example of display on a monitor in a case inwhich agent association does not exist;

FIG. 10 is a sequence chart illustrating an example of a flow ofprocessing to infer the intent of a question in a manual provisionsystem of the first exemplary embodiment;

FIG. 11 is a sequence chart (continued from FIG. 10) illustrating anexample of a flow of processing to infer the intent of a question in amanual provision system of the first exemplary embodiment;

FIG. 12 is a diagram illustrating an example of information relating toresponse information presented to an occupant;

FIG. 13 is a sequence chart illustrating an example of a flow ofprocessing to infer the intent of a question in a manual provisionsystem of a second exemplary embodiment;

FIG. 14 is a sequence chart (continued from FIG. 13) illustrating anexample of a flow of processing to infer the intent of a question in amanual provision system of the second exemplary embodiment; and

FIG. 15 is a block diagram illustrating an example of functionalconfigurations of an agent server of a third exemplary embodiment.

DETAILED DESCRIPTION First Exemplary Embodiment

As illustrated in FIG. 1, a manual provision system 10 configuring anagent system of a first exemplary embodiment includes plural vehicles 12and plural servers 30. An onboard device 20 serving as a notificationdevice is installed in each of the vehicles 12. The servers 30 include ahuman machine interface (hereafter “HMI”) server 14 serving as aninterface device with an HMI function, an agent server 16 serving as anagent device, an owner's manual (hereafter also abbreviated to OM)server 18, and a data server 19.

The onboard devices 20 of the respective vehicles 12, the HMI server 14,the OM server 18, and the data server 19 are connected together througha network N1. The HMI server 14 and the agent server 16 are connectedtogether through a network N2. Note that the agent server 16 may also beconnected to the network N1, similarly to the other servers 30.

Vehicle

As illustrated in FIG. 2, each of the vehicles 12 according to thepresent exemplary embodiment includes the onboard device 20, plural ECUs22, a microphone 24 serving as an audio input device, an input switch 26serving as an operation input device, a monitor 28 serving as a displaydevice, and a speaker 29.

The onboard device 20 includes a central processing unit (CPU) 20A, readonly memory (ROM) 20B, random access memory (RAM) 20C, an in-vehiclecommunication interface (I/F) 20D, a wireless communication I/F 20E, andan input/output I/F 20F. The CPU 20A, the ROM 20B, the RAM 20C, thein-vehicle communication I/F 20D, the wireless communication I/F 20E,and the input/output I/F 20F are connected together through an internalbus 20G so as to be capable of communicating with each other.

The CPU 20A is a central processing unit that executes various programsand controls various sections. Namely, the CPU 20A reads a program fromthe ROM 20B, and executes the program using the RAM 20C as a workspace.

The ROM 20B stores various programs and various data. The ROM 20B of thepresent exemplary embodiment is stored with a control program used tocontrol the onboard device 20.

The RAM 20C serves as a workspace that temporarily stores programs anddata.

The in-vehicle communication I/F 20D is an interface for connecting tothe ECUs 22. This interface employs a CAN communication protocol. Thein-vehicle communication I/F 20D is connected to an external bus 20Hserving as a communication path. The ECUs 22 serve as control devices,and plural thereof are provided corresponding to respectivefunctionality of the vehicle 12. Examples of the ECUs 22 of the presentexemplary embodiment include a vehicle control ECU, an engine ECU, abrake ECU, a body ECU, a camera ECU, and a multimedia ECU.

The wireless communication I/F 20E is a wireless communication moduleused to communicate with the servers 30. The wireless communicationmodule employs a communication protocol such as 5G; LTE, or Wi-Fi(registered trademark). The wireless communication I/F 20E is connectedto the network N1.

The input/output I/F 20F is an interface used to communicate with themicrophone 24, the input switch 26, the monitor 28, and the speaker 29installed in the vehicle 12.

The microphone 24 is provided in a front pillar, dashboard, or the likeof the vehicle 12, and is a device that picks up sound emanating from auser, namely an occupant of the vehicle 12.

The input switch 26 is provided to an instrument panel, a centerconsole, a steering wheel, or the like, and is a switch configured forinput operation by a finger of the occupant. For example, a push buttonten-key pad or a touch pad may be employed as the input switch 26.

The monitor 28 is provided to the instrument panel, a meter panel, orthe like, and is a liquid crystal monitor used to display imagesrelating to an owner's manual and response information, described later.The monitor 28 may be provided in the form of a touch panel that doublesas the input switch 26.

The speaker 29 is provided in the instrument panel, center console,front pillar, dashboard, or the like, and is a device used to outputaudio relating to response information.

Servers

As illustrated in FIG. 3, each of the servers 30 includes a CPU 30A,this being an example of a hardware processor, ROM 30B corresponding tomemory, RAM 30C, storage 30D, and a communication I/F 30E. The CPU 30A,the ROM 30B, the RAM 30C, the storage 30D, and the communication I/F 30Eare connected together through an internal bus 30G so as to be capableof communicating with each other. The CPU 30A, the ROM 30B, the RAM 30C,and the communication I/F 30E have functionality equivalent to that ofthe CPU 20A, the ROM 20B, the RAM 20C, and the wireless communicationI/F 20E of the onboard device 20 described above.

The storage 30D includes a hard disk drive (HDD) or a solid state drive(SSD), and is stored with various programs and various data.

The CPU 30A functions as an OMA interaction control section 36, namely areception section 50, an acquisition section 52, a confirmation section53, an instruction section 54, a provision section 56, and as an intentinference section 38, by loading a program from the storage 30D andexecuting this program using the RAM 30C as a workspace.

A processing program 100 and a data group 110 are stored in the storage30D of the present exemplary embodiment. The processing program 100 is aprogram for implementing the various functionality included in theserver 30.

HMI Server

The HMI server 14 includes functionality to receive questions from theonboard device 20, and to refer to the agent server 16 for a response toa question relating to an owner's manual.

As illustrated in FIG. 5, the CPU 30A of the HMI server 14 of thepresent exemplary embodiment executes the processing program 100 so asto function as an HMI interaction control section 32, serving as aselection section.

The HMI interaction control section 32 communicates with the onboarddevice 20. The HMI interaction control section 32 acquires audioinformation from the occupant of the vehicle 12 transmitted from theonboard device 20, performs speech recognition, and converts the audioinformation to text information. Note that in the present exemplaryembodiment, it is anticipated that questions are asked in the form ofutterances from the occupant of the vehicle 12. Accordingly, audioinformation relating to an occupant utterance serves as inputinformation input to the onboard device 20 by the occupant. Inputinformation is configured by audio information relating to a questionuttered by the occupant, for example “How do I turn off this lamp?” or“What is the switch with an A in a circle?”.

The HMI interaction control section 32 also interprets the intent of theoccupant utterance based on the converted text information. In cases inwhich the HMI interaction control section 32 interprets that theoccupant has asked a question relating to the owner's manual, the HMIinteraction control section 32 refers to the agent server 16 regardingthis question. The HMI interaction control section 32 also transmitstext information relating to this question to the agent server 16, andreceives response information relating to the response from the agentserver 16.

The HMI interaction control section 32 also transmits the responseinformation received from the agent server 16 to the onboard device 20.Note that the response information includes both text information andaudio information relating to a response to the question. The textinformation includes a URL used to view HTML data from the owner'smanual.

The HMI server 14 also includes functionality to confirm an associationstatus of an agent (owner's manual agent; hereafter OMA) handling thequestion relating to the owner's manual, based on vehicle informationacquired from the onboard device 20. This functionality will bedescribed in detail later.

Agent Server

The agent server 16 functions as an OMA. The agent server 16 acquiresvehicle information for the corresponding vehicle 12 and textinformation relating to the question from the HMI server 14, and alsoacquires CAN information, this being state information relating to astate of the vehicle 12, from the data server 19. The agent server 16also provides the HMI server 14 with response information relating tothe response to the question.

In the agent server 16 of the present exemplary embodiment, the CPU 30Aexecutes the processing program 100 so as to function as the OMAinteraction control section 36 and the intent inference section 38illustrated in FIG. 4. The OMA interaction control section 36 includesthe reception section 50, the acquisition section 52, the confirmationsection 53, the instruction section 54, and the provision section 56.

The data group 110 of the agent server 16 includes vehicle-to-OMassociation data 200, intent inference ID management data 210, QA data220, word normalization data 230, and trained models 240, as illustratedin FIG. 5.

The vehicle-to-OM association data 200 is data in which vehicleinformation relating to the vehicle identification number, vehicle type,grade, equipment and so on of each of the vehicles 12 is stored inassociation with OM item codes allocated to respective owner's manuals.The vehicle-to-OM association data 200 is an example of a databasestoring association statuses of manuals stored with question responsesto respective vehicles.

The intent inference ID management data 210 is data in which associationrelationships between the OM item codes and intent inference engines arestored. In the intent inference ID management data 210, intent inferenceengine IDs are stored in association with the respective OM item codes.The intent inference engine IDs are IDs allocated to respective intentinference engines used during the execution of intent inferenceprocessing, described later. Individual intent inference engines areprovided for similar or related owner's manuals.

The QA data 220 is data in which response information is held linked tointent labels allocated to each response. Note that the intent labelsare label numbers provided as a result of inferring intent from contentuttered by an occupant. The response information relates to responses toquestions, and includes text for display, images for display, text fortext-to-speech readout, information regarding URLs to display owner'smanuals, and so on.

The word normalization data 230 is data employed to normalize words, andis used in a pre-processing stage before intent inference processing.This pre-processing refers to processing to standardize differences innotation and phrasing. For example, the word normalization data 230 mayinclude data for standardizing differences in notation, such asinformation indicating that “off” and “OFF” correspond to the same word.As another example, the word normalization data 230 may include data forstandardizing differences in phrasing, such as information indicatingthat “tire pressure warning lamp” and “air pressure warning lamp” referto the same thing.

The trained model 240 is data generated by performing machine learningemploying training data based on past states of the vehicle 12 prior toa reception timing when the reception section 50, described later,received text information, and on past occupant questions. The input ofthe training data is CAN information relating to past states of thevehicle 12, and text information relating to plural expressions relevantto questions during these past states, and an intent label relating to acorrect response to this question is the output. The CAN informationrelating to past states is an example of past state information. One ofthe trained models 240 is trained in advance for each intent inferenceengine.

FIG. 6 illustrates an example of training data based on past questionsand past CAN information. As illustrated in FIG. 6, the onboard device20 stores CAN information-based illumination states of warning lamps anddisplay lamps and notification states of notification sounds for thecorresponding vehicle 12. The onboard device 20 also stores audio inputto the microphone 24.

Note that when the onboard device 20 receives an occupant utterance, theonboard device 20 also acquires active illumination state andnotification state items from the CAN information for a determinationperiod running from a timing A that is a predetermined duration prior toa reception timing B, up to the timing B. In the example in FIG. 6,during the predetermined duration from the timing A to the timing B, adisplay 1, a display 2, and a notification sound 1 are ON, in otherwords are active. The training data generates input data in which afeature amount of “1” is applied to any element that is active for apredetermined duration or longer during the determination period.

The uttered question is converted to text by speech recognition, andwords are extracted therefrom. Extracted candidate words correspond to“expressions”. In the example of FIG. 6, since a word 2 is included inthe utterance, the feature amount of “1” is applied to the word 2 in thegenerated input data.

As output, intent labels associated with the intent of the utterance areapplied to the input applied with feature amounts as described above. Inthe example of FIG. 6, a No. 1 intent label is associated with theinput. In the above-described example of the present exemplaryembodiment, in a case in which a question including the word 2 is askedwhen the display 1, the display 2, and the notification sound 1 are inactive states, machine learning is performed using training data so asto generate the No. 1 intent label in response to this question.

In the OMA interaction control section 36 illustrated in FIG. 5, firstlythe reception section 50 receives text information configuring questioninformation, and also receives vehicle information. The receptionsection 50 is also capable of receiving the CAN information relating tothe state of the vehicle 12. Next, in cases in which the textinformation corresponds to a question from the occupant, the acquisitionsection 52 of the OMA interaction control section 36 acquires a responseto the question based on the vehicle information, the CAN information,and the text information. The acquired response is obtained byperforming intent inference processing to infer the intent of thequestion.

More specifically, the acquisition section 52 consults the vehicle-to-OMassociation data 200 to acquire the OM item code associated with a givenvehicle 12 based on the vehicle information for this vehicle 12. Incases in which the acquisition section 52 is unable to acquire an OMitem code, the acquisition section 52 notifies the HMI interactioncontrol section 32 that “this service is unavailable”. The acquisitionsection 52 also consults the intent inference ID management data 210 toacquire the OMA intent inference engine ID applicable to the givenvehicle 12 based on the acquired OM item code.

The acquisition section 52 then refers to the intent inference section38 using input values of the text information relating to the question,the CAN information of the vehicle 12, and the OMA intent inferenceengine ID, and acquires an intent label corresponding to a response. Incases in which no intent label could be acquired, the provision section56 transmits no-results information indicating that no results werefound to the HMI server 14. On the other hand, in cases in which asingle intent label has been acquired, the acquisition section 52consults the QA data 220 to acquire the associated response informationbased on the acquired intent label and the OM item code.

Note that in cases in which plural intent labels are acquired, theacquisition section 52 may consult the QA data 220 to generate optioninformation relating to plural response options. In cases in whichoption information is generated, this option information is transmittedto the onboard device 20, and result information, this being a resultselected by the occupant, can be acquired from the onboard device 20 inorder to identify a single intent label.

The confirmation section 53 of the OMA interaction control section 36includes functionality to confirm an association status of the vehicle12 to the OMA. As the OMA association status, confirmation may be madenot only as to whether or not generation of a response to any occupantquestion is possible, but also as to whether or not generation of aresponse to certain questions is possible. The confirmation section 53searches the vehicle-to-OM association data 200 and confirms the OMAassociation status based on the presence or absence of an OM item codeassociated with the vehicle information received by the receptionsection 50.

The instruction section 54 of the OMA interaction control section 36instructs the onboard device 20 such that the onboard device 20 blocksreceipt of questions falling within a scope for which the confirmationsection 53 has confirmed that response generation is not possible. Thefunctionality of the instruction section 54 will be described in detaillater.

The provision section 56 of the OMA interaction control section 36transmits one out of no-results information, response information, oroption information to the HMI interaction control section 32 of the HMIserver 14. More specifically, in cases in which the acquisition section52 has been unable to acquire an intent label, the acquisition section52 transmits no-results information to the HMI server 14. In cases inwhich the acquisition section 52 has acquired a single intent label, theacquisition section 52 transmits the associated response information tothe HMI server 14. In cases in which the acquisition section 52 hasacquired plural intent labels, the acquisition section 52 transmits thegenerated option information to the HMI server 14.

The intent inference section 38, serving as an inference section,executes intent inference processing as inference processing to inferthe intent of a question from an occupant. The intent inferenceprocessing is executed employing the intent inference engine associatedwith the intent inference engine ID. Specific explanation followsregarding execution of the intent inference processing. Firstly, theintent inference section 38 uses the word normalization data 230 toperform pre-processing on the text of the acquired text information. Thepre-processing standardizes differences in notation and differences inphrasing. Next, the intent inference section 38 inputs the trained model240 prepared for the corresponding intent inference engine with thepre-processed text information and the CAN information of the vehicle12, and outputs an intent label and confidence score. The confidencescore corresponds to a probability that the text information input tothe trained model 240 matches the inferred intent label. The intentinference section 38 then provides any intent labels having a confidencescore exceeding a predetermined value, namely intent labels vouched tohave at least a predetermined probability of dependability, to the OMAinteraction control section 36.

OM Server

The OM server 18 is a server 30 that provides an owner's manual. Thedata group 110 of the OM server 18 includes OM data 300, this being HTMLdata relating to owner's manuals. In a case in which an image relatingto response information is displayed on the monitor 28 of the vehicle12, the occupant selects a URL included in the image to execute atransmission request for HTML data associated with the URL to the OMserver 18. The HTML data of the owner's manual associated with the URLis thus transmitted to the onboard device 20 to be displayed on themonitor 28.

Data Server

The data server 19 is a server 30 that acquires CAN information from theonboard device 20, and provides CAN information to the agent server 16.The CPU 30A of the data server 19 of the present exemplary embodimentexecutes the processing program 100 so as to function as a datamanagement section 39.

The data group 110 of the data server 19 includes a CAN database 400configured of data including vehicle information of the respectivevehicles 12 and CAN information associated with the vehicle information.The data management section 39 acquires the CAN information for therespective vehicles 12 from the onboard devices 20 at predeterminedintervals, and stores this in the CAN database 400. The data managementsection 39 also provides CAN information to the agent server 16 whenrequested to do so by the agent server 16.

Note that by acquiring CAN information and audio information relating toquestions from the onboard devices 20, the data management section 39 ofthe data server 19 is able to generate training data to generate newtrained models 240 by performing machine learning. The new trainedmodels 240 thus generated are transmitted to the agent server 16 asupdates.

Control Flow

(1) Processing Relating to Agent Association Status Confirmation andProcessing to Reflect Association Status on Monitor

Explanation follows regarding processing performed for the respectivevehicles 12, including processing relating to OMA association statusconfirmation and processing to reflect this association status on themonitor 28, with reference to the sequence chart of FIG. 7.

Firstly, explanation follows regarding processing to confirm the OMAassociation status.

At step S10 in FIG. 7, the onboard device 20 detects start-up of thecorresponding vehicle 12. Start-up here refers to a state in which anaccessory switch (ACC) has been turned ON.

At step S11, the onboard device 20 transmits vehicle information of thevehicle 12 to the HMI server 14.

At step S12, the HMI interaction control section 32 of the HMI server 14orders confirmation of the OMA association status. Namely, the HMIinteraction control section 32 sends a confirmation request to the agentserver 16.

At step S13, the HMI interaction control section 32 transmits vehicleinformation to the OMA interaction control section 36 of the agentserver 16.

At step S14, the OMA interaction control section 36 searches the OM itemcodes. More specifically, the OMA interaction control section 36consults the vehicle-to-OM association data 200 to search for whether ornot an OM item code associated with the acquired vehicle information ispresent.

At step S15, the OMA interaction control section 36 confirms whether ornot an OMA association exists. More specifically, in cases in which theOMA interaction control section 36 is able to find an OM item codeassociated with the vehicle information, the OMA interaction controlsection 36 confirms that an association exists, and in cases in whichthe OMA interaction control section 36 is unable to find an OM item codeassociated with the vehicle information, the OMA interaction controlsection 36 confirms that an association does not exist.

At step S16, the OMA interaction control section 36 notifies the onboarddevice 20 of the association status via the HMI server 14.

At step S17, the onboard device 20 updates the presence or absence ofOMA association.

Next, explanation follows regarding processing to reflect the OMAassociation status on the monitor 28.

At step S20 in FIG. 7, the onboard device 20 receives an utterance. Forexample, suppose the occupant of the vehicle 12 says “My agent”, thisbeing a keyword used to start up the agent, into the microphone 24.

When this is performed, at step S21, the onboard device 20 displays aninitial screen relating to agent functionality on the monitor 28. FIG. 8and FIG. 9 are examples of the initial screen displayed on the monitor28. Plural input buttons 80 relating to functionality of the onboarddevice 20 are displayed on the monitor 28. The input buttons 80 includea navigation button 80A, an audio button 80B, a phone call button 80C, avehicle function button 80D, and a help button 80E. In the presentexemplary embodiment, the help button 80E is associated with an OMA.

When the initial screen is displayed on the monitor 28, in cases inwhich OMA association exists, as illustrated in FIG. 8 the help button80E is displayed as active and is selectable. On the other hand, whenthe initial screen is displayed on the monitor 28, in cases in which OMAassociation does not exist, as illustrated in FIG. 9 the help button 80Edisplay is grayed out and is not selectable. In such cases, the onboarddevice 20 is unable to receive questions relating to functionality ofthe vehicle 12 when the display has been grayed out.

(2) Processing to Present Response to Question

Explanation follows regarding processing performed when the occupant ofthe vehicle 12 has asked a question, up to and including presentation ofa response, with reference to the sequence charts of FIG. 10 and FIG.11.

At step S30 in FIG. 10, the onboard device 20 acquires CAN informationthrough the external bus 20H.

At step S31, the onboard device 20 transmits the acquired CANinformation to the data server 19 together with vehicle information ofthe vehicle 12. Note that although in the present exemplary embodimentthe vehicle information and the CAN information are transmitted from theonboard device 20 to the data server 19 at predetermined intervals,there is no limitation thereto, and transmission from the onboard device20 to the data server 19 may be performed whenever the CAN informationchanges.

At step S32, the data server 19 stores the information acquired by thedata management section 39 in the CAN database 400. The storedinformation includes vehicle information, CAN information, and areception timestamp.

At step S40, the onboard device 20 receives an utterance from theoccupant. More specifically, the CPU 20A of the onboard device 20acquires audio uttered into the microphone 24 by the occupant as audioinformation. For example, suppose that the occupant utters the phrase “Ameter lamp has come on, but what does it mean?” in a state in which atire pressure warning lamp of the vehicle 12 has lit up. When this isperformed, the utterance is received such that the utterance of “A meterlamp has come on, but what does it mean” is acquired as audioinformation.

At step S41, the onboard device 20 transmits the acquired audioinformation to the HMI server 14 together with vehicle information ofthe vehicle 12 and an utterance start timestamp.

At step S42, the HMI interaction control section 32 of the HMI server 14performs speech recognition. The audio information is thus convertedinto text information. Note that when this speech recognition isperformed, the audio information is determined to be a question in casesin which a linguistic feature corresponding to a question is included inthe text information.

At step S43, the HMI interaction control section 32 transmits thevehicle information, the utterance start timestamp, and the textinformation to the OMA interaction control section 36 of the agentserver 16. In the above example, the text string “A meter lamp has comeon, but what does it mean” that has been determined to be a question istransmitted as the text information.

At step S44, the OMA interaction control section 36 searches for CANinformation. Namely, the OMA interaction control section 36 attempts toacquire CAN information from the data server 19.

At step S45, the OMA interaction control section 36 transmits thevehicle information and the utterance start timestamp to the data server19.

At step S46, the data management section 39 of the data server 19transmits CAN information or no-information notification to the agentserver 16. The transmitted CAN information is acquired by the datamanagement section 39 referring to the CAN database 400 and searchingfor CAN information relating to the vehicle information of the vehicle12 and also relating to a reception timestamp just before the utterancestart timestamp. Note that the no-information notification isnotification to indicate that there is no CAN information in cases inwhich CAN information associated with the vehicle information and theutterance start timestamp could not be acquired.

At step S47, the OMA interaction control section 36 identifies anassociated OM item code based on the vehicle information. Namely, theOMA interaction control section 36 identifies an owner's manualassociated with the vehicle identification number, vehicle type, grade,equipment, or the like of the vehicle 12. Note that the CAN informationmay also be employed to identify the OM item code. In such cases, if theOMA interaction control section 36 is unable to acquire the newest CANinformation of the vehicle 12 as a result of poor communication or thelike, the OM item code considered standard for the vehicle type or grademay be identified.

At step S48, the OMA interaction control section 36 identifies theassociated intent inference engine ID based on the OM item code. Namely,the intent inference engine associated with the owner's manual of thevehicle 12 is identified. Note that CAN information may also be employedto identify the intent inference engine ID. In such cases, if the OMAinteraction control section 36 is unable to acquire the newest CANinformation of the vehicle 12 as a result of poor communication or thelike, the intent inference engine ID considered standard for the vehicletype or grade may be identified.

At step S49, the OMA interaction control section 36 provides the textinformation acquired from the HMI server 14, the CAN informationacquired from the data server 19, and the intent inference engine ID tothe intent inference section 38.

At step S50, the intent inference section 38 executes intent inferenceprocessing. The intent inference section 38 thus outputs intent labelsassociated with the text information and the CAN information. In theexample of the present exemplary embodiment, intent labels associatedwith the intent inferred from the text information of “A meter lamp hascome on, but what does it mean” are output.

Moving on to FIG. 11, at step S51, the intent inference section 38provides the OMA interaction control section 36 with the single intentlabel with the highest confidence score. Note that in cases in which anintent label with a confidence score exceeding the predetermined valueis not output, the intent inference section 38 provides the OMAinteraction control section 36 with no-label information to indicatethat no intent label has been returned.

At step S52, the OMA interaction control section 36 generates responseinformation based on the intent label. Namely, the OMA interactioncontrol section 36 consults the QA data 220 to generate responseinformation configured by a combination of text for display, images fordisplay, text for text-to-speech readout, a URL to display the owner'smanual, and the like.

At step S53, the OMA interaction control section 36 transmits theresponse information to the HMI server 14.

At step S54, the HMI interaction control section 32 generatespresentation information. The presentation information is informationfor transmission to the onboard device 20, and is response informationfrom which information that does not need to be presented using themonitor 28 or the speaker 29, for example the intent label, the OM itemcode, and the like, has been cut. Note that the response information mayalso be employed as-is as the presentation information.

At step S55, the HMI interaction control section 32 transmits thepresentation information to the onboard device 20.

At step S56, the onboard device 20 presents the received presentationinformation to the occupant of the vehicle 12. More specifically, theCPU 20A of the onboard device 20 displays images relating to thereceived presentation information on the monitor 28, and outputs audiorelating to the received presentation information from the speaker 29.For example, as illustrated in FIG. 12, the CPU 20A di splays anexplanation regarding the tire pressure warning system on the monitor28, and outputs “That is a warning from the tire pressure warningsystem” as audio from the speaker 29.

Summary of First Exemplary Embodiment

The manual provision system 10 of the present exemplary embodiment iscapable of providing a response to the onboard device 20 obtained byinferring the intent of the question when the occupant of the vehicle 12asks a question which is input via the onboard device 20.

In the agent server 16 of the present exemplary embodiment, thereception section 50 that receives text information receives vehicleinformation when the vehicle 12 is started up. Based on the vehicleinformation, the confirmation section 53 confirms a scope of questionsfor which response generation is not possible. Note that cases in which“response generation is not possible” include cases in which an owner'smanual stored with responses to questions has not been compiled, andcases in which an owner's manual is temporarily unavailable due to anongoing update. The instruction section 54 instructs the onboard device20 such that the onboard device 20 blocks receipt of questions fallingwithin the scope for which the confirmation section 53 has confirmedthat response generation is not possible. Accordingly, the presentexemplary embodiment is capable of suppressing a sense of frustrationfelt by the occupant in cases in which response generation is notpossible for questions regarding some or all functionality.

Since the scope of questions for which response generation is notpossible is confirmed at the point when the vehicle 12 is started up,questions are not received in error, thus enabling a sense offrustration felt by the user to be suppressed. Note that the vehicleinformation reception timing does not necessarily have to be when thevehicle 12 is started up.

Moreover, the confirmation section 53 of the agent server 16 of thepresent exemplary embodiment searches the vehicle-to-OM association data200 in which the associations between owner's manuals and correspondingvehicles 12 are stored in order to confirm the scope of questions forwhich response generation is not possible. In the present exemplaryembodiment, compiling a database regarding the availability orunavailability of an owner's manual for each vehicle 12 enables simplermanagement to block receipt of questions for which response generationis not possible by the onboard device 20.

The reception section 50 of the agent server 16 of the present exemplaryembodiment receives CAN information of the vehicle 12 in addition toquestion information. The intent inference section 38 performs intentinference processing as inference processing employing both textinformation and CAN information, and the acquisition section 52 acquiresa response to the question based on the inferred intent. The agentserver 16 of the present exemplary embodiment is capable of taking thestate of the vehicle 12 into account when inferring the intent of aquestion, enabling the precision with which intent is inferred to beimproved.

Moreover, the agent server 16 of the present exemplary embodiment infersintent using the trained model 240 generated in advance by the intentinference section 38 performing machine learning. The present exemplaryembodiment enables training using more information regarding thevehicles 12 and expressions, thereby enabling the precision with whichthe intent of an occupant's question is inferred to be improved. Notethat in the data server 19, extra machine learning may be performed byacquiring CAN information and response results to questions in order togenerate new trained models 240. Moreover, the trained models 240 of theagent server 16 are updated, enabling the inference precision to befurther improved.

The agent server 16 of the present exemplary embodiment is capable ofacquiring CAN information of the vehicle 12 through the external bus 20Hthat connects the plural ECUs 22 that control the vehicle 12 together.In the present exemplary embodiment, utilizing this vehicle controlcommunication information enables simple acquisition of the state of thevehicle 12 from the vehicle 12.

In the agent server 16 of the present exemplary embodiment, asillustrated in FIG. 6, machine learning is performed based on the stateof the vehicle 12 during the predetermined duration. Accordingly, in thepresent exemplary embodiment, setting the predetermined duration to aduration in which, for example, the occupant will have had a chance tonotice a warning lamp or the like enables a state of the vehicle 12 ofwhich the occupant is likely to be conscious to be taken into accountwhen inferring the intent.

In the manual provision system 10 according to the present exemplaryembodiment, the onboard device 20 installed to the vehicle 12 is capableof providing a response to a question from the occupant. The presentexemplary embodiment is thus capable of enhancing convenience ofoperation for the occupant of the vehicle 12.

In the present exemplary embodiment, the onboard device 20 is configuredto gray out display of an input button 80 on the monitor 28 asillustrated in FIG. 9, and block reception of operation through theinput button 80. The present exemplary embodiment is thus capable ofvisually conveying to the occupant when the agent is not available.

Note that although in the present exemplary embodiment explanation hasbeen given in which the corresponding input button 80 is grayed out whenblocked from receiving operation, there is no limitation thereto. Forexample, text reading “unavailable” or the like may be displayedoverlaid on the input button 80.

The onboard device 20 of the present exemplary embodiment may alsodisplay text reading “preparing . . . ”, “loading . . . ” or similaradjacent to or overlaid on the corresponding input button 80 in cases inwhich an owner's manual associated with the vehicle 12 is about tobecome available. In cases in which the onboard device 20 has completedprocurement of an owner's manual associated with the vehicle 12, textsuch as “new” or “available today!” may be displayed adjacent to oroverlaid on the corresponding input button 80. Moreover, the onboarddevice 20 may change the color of the input button 80 over time, orgradually reduce the grayed out effect, as the owner's manual associatedwith the vehicle 12 transitions from being in the process of beingprocured to procurement being completed. “Procurement” of the owner'smanual refers to adding the associated owner's manual to the OM data 300of the OM server 18 and adding information associated with the owner'smanual of the vehicle 12 to the vehicle-to-OM association data 200 ofthe agent server 16.

Second Exemplary Embodiment

In the first exemplary embodiment, the intent inference processing isexecuted based on text information and CAN information, and a singleintent label is acquired. By contrast, in a second exemplary embodiment,plural intent labels are acquired during the intent inferenceprocessing, and the CAN information is consulted to execute intentidentification processing to narrow down to a single intent label.Namely, the intent inference processing and the intent identificationprocessing are executed as the inference processing. Explanation followsregarding points that differ from the first exemplary embodiment in theprocessing performed in order to present a response to a question.

Explanation follows regarding processing performed in the presentexemplary embodiment from when the occupant of the vehicle 12 asks aquestion until presentation of a response, with reference to thesequence charts of FIG. 13 and FIG. 14.

The processing from step S60 to step S63 in FIG. 13 matches theprocessing of step S40 to step S43 in FIG. 10.

At step S64, the OMA interaction control section 36 identifies the OMitem code associated with the vehicle information. Namely, an owner'smanual associated with the vehicle identification number, vehicle type,grade, equipment, or the like of the vehicle 12 is identified.

At step S65, the OMA interaction control section 36 identifies theintent inference engine ID associated with the OM item code. Namely, theintent inference engine associated with the owner's manual of thevehicle 12 is identified.

At step S66, the OMA interaction control section 36 provides the textinformation and the intent inference engine ID acquired from the HMIserver 14 to the intent inference section 38.

At step S67, the intent inference section 38 executes the intentinference processing, this being one part of the inference processing.The intent inference section 38 thereby outputs intent labels associatedwith the text information. For example, plural intent labels associatedwith the inferred intent of the text information “A meter lamp has comeon, but what does it mean” are output.

Moving on to FIG. 14, at step S68, the intent inference section 38provides the OMA interaction control section 36 with plural intentlabels that have confidence scores exceeding a predetermined value. Notethat in cases in which no intent labels with a confidence scoreexceeding the predetermined value are output, the intent inferencesection 38 provides the OMA interaction control section 36 with no-labelinformation to indicate that no intent labels have been returned.

At step S69, the OMA interaction control section 36 determines whetheror not any CAN information that should be consulted is present. Forexample, suppose that as a result of the intent inference processing,intent labels relating to warning lamps relevant to a display 1, adisplay 2, and a display 10 are acquired. In such cases, since CANinformation relating to these warning lamps can be consulted, CANinformation that should be consulted is determined to be present. TheOMA interaction control section 36 proceeds to step S70 in cases inwhich CAN information that should be consulted is determined to bepresent. On the other hand, the OMA interaction control section 36proceeds to step S74 in cases in which CAN information that should beconsulted is determined not to be present.

At step S70, the OMA interaction control section 36 searches for the CANinformation. Namely, the OMA interaction control section 36 attempts toacquire CAN information from the data server 19.

At step S71, the OMA interaction control section 36 transmits thevehicle information and the utterance start timestamp to the data server19.

At step S72, the data management section 39 of the data server 19transmits the CAN information or the no-information notification to theagent server 16. Specific details of this step match those of step S46in FIG. 10.

At step S73, the OMA interaction control section 36, serving as anidentification section, executes the intent identification processing,this being one element of the inference processing using the CANinformation. From the plural intent labels, the OMA interaction controlsection 36 acquires a single intent label associated with the CANinformation. For example, in cases in which CAN information indicatingthat the tire pressure warning lamp has lit up has been acquired, anintent label relating to the tire pressure warning system is acquiredfrom out of the plural intent labels. Namely, inference processing isexecuted by the intent inference processing performed by the intentinference section 38 and by the intent identification processingperformed by the OMA interaction control section 36.

The subsequent processing from step S74 to step S78 matches theprocessing of step S52 to step S56 in FIG. 11.

By performing the above processing, the manual provision system 10 ofthe present exemplary embodiment is capable of obtaining similaradvantageous effects to those of the first exemplary embodiment.

Third Exemplary Embodiment

In the first exemplary embodiment and the second exemplary embodiment,the HMI server 14, the agent server 16, and the data server 19 areconfigured by different servers 30. By contrast, in a third exemplaryembodiment, the HMI server 14 and the data server 19 are consolidated inthe agent server 16, as illustrated in FIG. 15.

The manual provision system 10 of the present exemplary embodiment isalso capable of obtaining similar advantageous effects to those of thefirst and second exemplary embodiments.

Remarks

In the exemplary embodiments described above, audio information based onan utterance of an occupant configures the input information of the HMIserver 14. However, there is no limitation thereto, and the inputinformation may be configured by operation information based onoperation of the touch panel configuring the monitor 28 by the occupant.In such cases, the operation information is, for example, textinformation relating to a text string input to the monitor 28 by theoccupant.

In the third exemplary embodiment described above, the HMI server 14 andthe data server 19 included in the manual provision system 10 areconsolidated in the agent server 16. However, the OM server 18 may alsobe consolidated. Alternatively, the servers 30 configuring some out ofthe HMI server 14, the agent server 16, the OM server 18, and the dataserver 19 may be consolidated. Moreover, in the agent server 16, thefunctionality of the OMA interaction control section 36 and the intentinference section 38 may be distributed between different servers 30.

The various processing executed by the CPUs 20A, 30A reading software (aprogram) in the exemplary embodiments described above may be executed byvarious types of processor other than the CPUs. Such processors includeprogrammable logic devices (PLDs) that allow circuit configuration to bemodified post-manufacture, such as a field-programmable gate array(FPGA), and dedicated electric circuits, these being processorsincluding a circuit configuration custom-designed to execute specificprocessing, such as an application specific integrated circuit (ASIC).The processing described above may be executed by any one of thesevarious types of processor, or by a combination of two or more of thesame type or different types of processor (such as plural FPGAs, or acombination of a CPU and an FPGA). The hardware structure of thesevarious types of processors is more specifically an electric circuitcombining circuit elements such as semiconductor elements.

The exemplary embodiments described above have described implementationsin which the program is in a format pre-stored (installed) in acomputer-readable non-transitory recording medium. For example, theprocessing program 100 of each of the servers 30 is pre-stored in thecorresponding storage 30D. However, there is no limitation thereto, andthe respective programs may be provided in a format recorded on anon-transitory recording medium such as compact disc read only memory(CD-ROM), digital versatile disc read only memory (DVD-ROM), oruniversal serial bus (USB) memory. Alternatively, the program may beprovided in a format downloadable from an external device through anetwork.

Instead of being executed by a single processor, the processing of theexemplary embodiments described above may be executed by pluralprocessors working collaboratively. The processing flows explained inthe above exemplary embodiment are merely examples, and superfluoussteps may be omitted, new steps may be added, or the processingsequences may be changed within a range not departing from the spirit ofthe present disclosure.

An object of the present disclosure is to provide an agent device, anagent system, and a non-transitory recording medium capable of reducinga sense of frustration felt by a user in cases in which an agentconfigured to infer the intent of a question regarding vehiclefunctionality is unable to provide agent support for some or allfunctionality.

A first aspect of the disclosure is an agent device that includes: amemory; and a processor coupled to the memory. The processor isconfigured to: receive, from an onboard device installed in a vehicle,vehicle information relating to the vehicle and question informationcorresponding to a question from a user, based on the vehicleinformation, confirm a scope of questions for which generation of aresponse is not possible, and instruct the onboard device to blockreceipt of questions falling within the scope of questions for which ithas been confirmed that response generation is not possible.

The agent device of the first aspect is capable of providing the userwith a response to the question from the user. The agent device thatreceives the question information also receives the vehicle informationenabling the vehicle to be identified. Based on the vehicle information,the agent device confirms the scope of questions for which the responsegeneration is not possible. Note that cases in which “responsegeneration is not possible” include cases in which a manual stored withresponses to questions has not been compiled, and cases in which amanual is temporarily unavailable due to an ongoing update. The agentdevice instructs the onboard device to block receipt of questionsfalling within the scope of questions for which the agent device hasconfirmed that response generation is not possible. Accordingly, theagent device is capable of reducing a sense of frustration felt by theuser in cases in which the response generation is not possible forquestions regarding some or all functionality.

A second aspect of the disclosure is the agent device of the firstaspect, wherein the processor is configured to search a database storingstate information indicating correspondence, to respective vehicles, ofmanuals storing responses, and to confirm the scope of questions forwhich response generation is not possible based on presence or absenceof a manual corresponding to the vehicle information.

The agent device of the second aspect searches the database in which theassociations between the manuals and the vehicles are stored in order toconfirm the scope of questions for which response generation is notpossible. In this agent device, compiling the database regarding theavailability or unavailability of a manual for each vehicle enablessimpler management to block receipt of questions for which the responsegeneration is not possible by the onboard device.

A third aspect of the disclosure is the agent device of the firstaspect, wherein the processor is configured to confirm the scope ofquestions for which response generation is not possible at a time ofstart-up of the vehicle.

In the agent device of the third aspect, since the scope of questionsfor which the response generation is not possible is confirmed at thepoint when the vehicle is started up, questions are not received inerror, thus enabling a sense of frustration felt by the user to bereduced.

A fourth aspect of the disclosure is an agent system that includes anagent device and an onboard device. The agent device includes a memoryand a processor coupled to the memory. The processor is configured toreceive, from an onboard device installed in a vehicle, vehicleinformation relating to the vehicle and question informationcorresponding to a question from a user, based on the vehicleinformation, confirm a scope of questions for which generation of aresponse is not possible, and instruct the onboard device to blockreceipt of questions falling within the scope of questions for which ithas been confirmed that response generation is not possible. The onboarddevice is configured to control a display device provided to the vehicleso as to gray out an input button relating to the question wheninstructed by the agent device to block receipt.

In the agent system of the fourth aspect, the onboard device installedin the vehicle is configured to gray out display of the input button onthe display device and block reception of operation through the inputbutton. This agent system is thus capable of visually conveying to anoccupant when an agent is not available.

A fifth aspect of the disclosure is a non-transitory recording mediumthat stores a program to cause a computer to execute processing. Theprocessing includes: receiving, from an onboard device installed in avehicle, vehicle information relating to the vehicle on at a time ofstart-up of the vehicle, and receiving question informationcorresponding to a question from a user, based on the vehicleinformation, confirming a scope of questions for which generation of aresponse is not possible; and instructing the onboard device to blockreceipt of questions falling within the scope of questions for which ithas been confirmed that response generation is not possible.

The program recorded in the non-transitory recording medium of the fifthaspect is executable by a computer to perform processing to provide theuser with a response to the question from the user. The computerexecuting this program receives the vehicle information enabling thevehicle to be identified, and confirms the scope of questions for whichresponse generation is not possible based on the vehicle information.Cases in which “response generation is not possible” are as describedpreviously. The computer then instructs the onboard device to blockreceipt of questions falling within the scope for which the responsegeneration has been confirmed as not possible. Accordingly, this programis capable of reducing a sense of frustration felt by the user in casesin which the response generation is not possible for questions regardingsome or all functionality.

A sixth aspect of the disclosure is the non-transitory recording mediumof the fifth aspect, wherein the processing further comprises searchinga database storing state information indicating correspondence, torespective vehicles, of manuals storing responses, and confirming thescope of questions for which response generation is not possible basedon presence or absence of a manual corresponding to the vehicleinformation.

A seventh aspect of the disclosure is the non-transitory recordingmedium of the fifth aspect, wherein the processing further comprisesconfirming the scope of questions for which response generation is notpossible at a time of start-up of the vehicle.

In the present disclosure is capable of reducing a sense of frustrationfelt by a user in cases in which an agent configured to infer the intentof a question regarding vehicle functionality is unable to provide agentsupport for some or all functionality.

What is claimed is:
 1. An agent device comprising: a memory; and aprocessor coupled to the memory, the processor being configured to:receive, from an onboard device installed in a vehicle, vehicleinformation relating to the vehicle and question informationcorresponding to a question from a user, based on the vehicleinformation, confirm a scope of questions for which generation of aresponse is not possible, and instruct the onboard device to blockreceipt of questions falling within the scope of questions for which ithas been confirmed that response generation is not possible.
 2. Theagent device of claim 1, wherein the processor is configured to search adatabase storing state information indicating correspondence, torespective vehicles, of manuals storing responses, and to confirm thescope of questions for which response generation is not possible basedon presence or absence of a manual corresponding to the vehicleinformation.
 3. The agent device of claim 1, wherein the processor isconfigured to confirm the scope of questions for which responsegeneration is not possible at a time of start-up of the vehicle.
 4. Anagent system comprising: an agent device that includes a memory and aprocessor coupled to the memory, the processor being configured to:receive, from an onboard device installed in a vehicle, vehicleinformation relating to the vehicle and question informationcorresponding to a question from a user, based on the vehicleinformation, confirm a scope of questions for which generation of aresponse is not possible, and instruct the onboard device to blockreceipt of questions falling within the scope of questions for which ithas been confirmed that response generation is not possible; and theonboard device, which is configured to control a display device providedto the vehicle so as to gray out an input button relating to thequestion when instructed by the agent device to block receipt.
 5. Anon-transitory recording medium storing a program that is executable bya computer to perform processing, the processing comprising: receiving,from an onboard device installed in a vehicle, vehicle informationrelating to the vehicle on at a time of start-up of the vehicle, andreceiving question information corresponding to a question from a user,based on the vehicle information, confirming a scope of questions forwhich generation of a response is not possible; and instructing theonboard device to block receipt of questions falling within the scope ofquestions for which it has been confirmed that response generation isnot possible.
 6. The non-transitory recording medium of claim 5, whereinthe processing further comprises searching a database storing stateinformation indicating correspondence, to respective vehicles, ofmanuals storing responses, and confirming the scope of questions forwhich response generation is not possible based on presence or absenceof a manual corresponding to the vehicle information.
 7. Thenon-transitory recording medium of claim 5, wherein the processingfurther comprises confirming the scope of questions for which responsegeneration is not possible at a time of start-up of the vehicle.